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Leading Order Response of Statistical Averages of a Dynamical System to Small Stochastic Perturbations

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Abstract

The classical fluctuation-dissipation theorem predicts the average response of a dynamical system to an external deterministic perturbation via time-lagged statistical correlation functions of the corresponding unperturbed system. In this work we develop a fluctuation-response theory and test a computational framework for the leading order response of statistical averages of a deterministic or stochastic dynamical system to an external stochastic perturbation. In the case of a stochastic unperturbed dynamical system, we compute the leading order fluctuation-response formulas for two different cases: when the existing stochastic term is perturbed, and when a new, statistically independent, stochastic perturbation is introduced. We numerically investigate the effectiveness of the new response formulas for an appropriately rescaled Lorenz 96 system, in both the deterministic and stochastic unperturbed dynamical regimes.

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Notes

  1. The author privately communicated that his response formula applies to a perturbation noise in the Stratonovich form.

References

  1. Abramov, R.V.: Short-time linear response with reduced-rank tangent map. Chin. Ann. Math. 30B(5), 447–462 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  2. Abramov, R.V.: Approximate linear response for slow variables of deterministic or stochastic dynamics with time scale separation. J. Comput. Phys. 229(20), 7739–7746 (2010)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  3. Abramov, R.V.: Improved linear response for stochastically driven systems. Front. Math. China 7(2), 199–216 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  4. Abramov, R.V.: A simple linear response closure approximation for slow dynamics of a multiscale system with linear coupling. Multiscale Model. Simul. 10(1), 28–47 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  5. Abramov, R.V.: Suppression of chaos at slow variables by rapidly mixing fast dynamics through linear energy-preserving coupling. Commun. Math. Sci. 10(2), 595–624 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  6. Abramov, R.V.: A simple closure approximation for slow dynamics of a multiscale system: nonlinear and multiplicative coupling. Multiscale Model. Simul. 11(1), 134–151 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  7. Abramov, R.V.: Linear response of the Lyapunov exponent to a small constant perturbation. Commun. Math. Sci. 14(4), 1155–1167 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  8. Abramov, R.V.: A simple stochastic parameterization for reduced models of multiscale dynamics. Fluids 1(1), 2 (2016)

    Article  Google Scholar 

  9. Abramov, R.V., Kjerland, M.: The response of reduced models of multiscale dynamics to small external perturbations. Commun. Math. Sci. 14(3), 831–855 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  10. Abramov, R.V., Majda, A.J.: Blended response algorithms for linear fluctuation-dissipation for complex nonlinear dynamical systems. Nonlinearity 20, 2793–2821 (2007)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  11. Abramov, R.V., Majda, A.J.: New approximations and tests of linear fluctuation-response for chaotic nonlinear forced-dissipative dynamical systems. J. Nonlinear Sci. 18(3), 303–341 (2008)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  12. Abramov, R.V., Majda, A.J.: New algorithms for low frequency climate response. J. Atmos. Sci. 66, 286–309 (2009)

    Article  ADS  Google Scholar 

  13. Bell, T.: Climate sensitivity from fluctuation dissipation: some simple model tests. J. Atmos. Sci. 37(8), 1700–1708 (1980)

    Article  ADS  Google Scholar 

  14. Birkhoff, G.D.: Proof of the ergodic theorem. Proc. Natl. Acad. Sci. USA 17(12), 656–660 (1931)

    Article  ADS  MATH  Google Scholar 

  15. Carnevale, G., Falcioni, M., Isola, S., Purini, R., Vulpiani, A.: Fluctuation-response in systems with chaotic behavior. Phys. Fluids A 3(9), 2247–2254 (1991)

    Article  ADS  MATH  Google Scholar 

  16. Cohen, B., Craig, G.: The response time of a convective cloud ensemble to a change in forcing. Q. J. R. Meteorol. Soc. 130(598), 933–944 (2004)

    Article  ADS  Google Scholar 

  17. Eckmann, J.-P., Ruelle, D.: Ergodic theory of chaos and strange attractors. Rev. Mod. Phys. 57(3), 617–656 (1985)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  18. Evans, D., Morriss, G.: Statistical Mechanics of Nonequilibrium Liquids. Academic Press, New York (1990)

    MATH  Google Scholar 

  19. Gikhman, I.I., Skorokhod, A.V.: Introduction to the Theory of Random Processes. Courier Dover Publications, New York (1969)

    MATH  Google Scholar 

  20. Gikhman, I.I., Skorokhod, A.V.: The Theory of Stochastic Processes I. Classics in Mathematics. Springer, New York (2004)

    Google Scholar 

  21. Gritsun, A.: Fluctuation-dissipation theorem on attractors of atmospheric models. Russ. J. Numer. Math. Model. 16(2), 115–133 (2001)

    Google Scholar 

  22. Gritsun, A., Branstator, G.: Climate response using a three-dimensional operator based on the fluctuation-dissipation theorem. J. Atmos. Sci. 64, 2558–2575 (2007)

    Article  ADS  Google Scholar 

  23. Gritsun, A., Branstator, G., Dymnikov, V.: Construction of the linear response operator of an atmospheric general circulation model to small external forcing. Numer. Anal. Math. Model. 17, 399–416 (2002)

    MathSciNet  MATH  Google Scholar 

  24. Gritsun, A., Branstator, G., Majda, A.J.: Climate response of linear and quadratic functionals using the fluctuation dissipation theorem. J. Atmos. Sci. 65, 2824–2841 (2008)

    Article  ADS  Google Scholar 

  25. Gritsun, A., Dymnikov, V.: Barotropic atmosphere response to small external actions. Theory and numerical experiments. Atmos. Ocean Phys. 35(5), 511–525 (1999)

    Google Scholar 

  26. Itô, K.: Stochastic integral. Proc. Imp. Acad. Tokyo 20, 519–524 (1944)

    Article  MathSciNet  MATH  Google Scholar 

  27. Itô, K.: On stochastic differential equations. Mem. Am. Math. Soc. 4, 1–51 (1951)

    MathSciNet  Google Scholar 

  28. Kubo, R.: Statistical mechanical theory of irreversible processes I: general theory and simple applications to magnetic and conduction problems. J. Phys. Soc. Jpn. 12, 507–586 (1957)

    MathSciNet  Google Scholar 

  29. Kubo, R.: The fluctuation-dissipation theorem. Rep. Prog. Phys. 29, 255–284 (1966)

    Article  ADS  MATH  Google Scholar 

  30. Kubo, R., Toda, M., Hashitsume, N.: Statistical Physics II: Nonequilibrium Statistical Mechanics. Springer, New York (1985)

    Book  MATH  Google Scholar 

  31. Kunita, H.: Stochastic Flows and Stochastic Differential Equations. Cambridge University Press, Cambridge (1997)

    MATH  Google Scholar 

  32. Leith, C.: Climate response and fluctuation-dissipation. J. Atmos. Sci. 32, 2022–2025 (1975)

    Article  ADS  Google Scholar 

  33. Lorenz, E.: Predictability: a problem partly solved. In: Proceedings of the Seminar on Predictability, ECMWF, Shinfield Park, Reading, England (1996)

  34. Lorenz, E., Emanuel, K.: Optimal sites for supplementary weather observations. J. Atmos. Sci. 55, 399–414 (1998)

    Article  ADS  Google Scholar 

  35. Lucarini, V.: Stochastic perturbations to dynamical systems: a response theory approach. J. Stat. Phys. 146, 774–786 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  36. Lucarini, V., Sarno, S.: A statistical mechanical approach for the computation of the climatic response to general forcings. Nonlinear Process. Geophys. 18, 7–28 (2011)

    Article  ADS  Google Scholar 

  37. Majda, A.J., Abramov, R.V., Gershgorin, B.: High skill in low frequency climate response through fluctuation dissipation theorems despite structural instability. Proc. Natl. Acad. Sci. USA 107(2), 581–586 (2010)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  38. Majda, A.J., Abramov, R.V., Grote, M.J.: Information theory and stochastics for multiscale nonlinear systems, vol 25 of CRM Monograph Series of Centre de Recherches Mathématiques, Université de Montréal. American Mathematical Society (2005). ISBN 0-8218-3843-1

  39. Øksendal, B.: Stochastic Differential Equations: An Introduction with Applications. Universitext, 6th edn. Springer, New York (2010)

    Google Scholar 

  40. Pavliotis, G.: Stochastic Processes and Applications. Texts in Applied Mathematics, vol. 60. Springer, New York (2014)

    Google Scholar 

  41. Risken, H.: The Fokker-Planck Equation, 2nd edn. Springer, New York (1989)

    Book  MATH  Google Scholar 

  42. Ruelle, D.: Differentiation of SRB states. Commun. Math. Phys. 187, 227–241 (1997)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  43. Ruelle, D.: General linear response formula in statistical mechanics, and the fluctuation-dissipation theorem far from equilibrium. Phys. Lett. A 245, 220–224 (1998)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  44. Ruelle, D.: Nonequilibrium statistical mechanics near equilibrium: computing higher order terms. Nonlinearity 11, 5–18 (1998)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  45. Young, L.-S.: What are SRB measures, and which dynamical systems have them? J. Stat. Phys. 108(5–6), 733–754 (2002)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The work was supported by the Office of Naval Research Grant N00014-15-1-2036.

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Correspondence to Rafail V. Abramov.

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Abramov, R.V. Leading Order Response of Statistical Averages of a Dynamical System to Small Stochastic Perturbations. J Stat Phys 166, 1483–1508 (2017). https://doi.org/10.1007/s10955-017-1721-2

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